A new perspective on the solution of uncertainty quantification and reliability analysis of large-scale problems

Sensitivity analysis with MC simulation for the failure rate evaluation and reliability assessment

“…In addition to the example of data from field above mentioned, in a complex system as a process or plant other sources of uncertainty affect input data can be considered such as measurement errors for sensor wear or fault, poor information about equipment installation and work environment, environmental condition of use, maintenance activities, partial understanding of the driving forces and mechanisms, and so on [13][14][15][16][17][18][19]. Considering the incomplete knowledge of data, often acquired by fieldfield data of service as, for instance, maintenance information or failure informationor collected in database, and different sources of uncertainty, it is fundamental to identify model inputs that cause significant uncertainty in the output.…”

“…Best-fitting distribution in the six cases under analysis is lognormal (13) and gamma (14) distribution: Also in this case, the reliability function is considered with yearly frequency until sixth year to evaluate the evolution of the confidence interval.…”

Bayesian identification of the tendon fascicle’s structural composition using finite element models for helical geometries

“…Bayesian inference stands amongst the prevalent uncertainty quantification techniques that can fuse expert knowledge, past studies, physical modeling and experimental evidence. It is used for quantifying and calibrating uncertainty models, as well as propagating these uncertainties in engineering simulations to achieve updated robust predictions of the structural performance, reliability and safety [29,30,31,32,33].…”

Enhanced goal‐oriented error assessment and computational strategies in adaptive reduced basis solver for stochastic problems

“…Here, we complement the methodology with an error assessment strategy based on the residual of the equation solved for the new configuration, which is fully consistent with the RB approach. A different strategy that could be also treated within a similar framework is solving the full FE problem of the new configuration with a smart preconditioning based on previous solutions, see .…”